Agent skills
Skills you can use with AI coding agents, indexed from public GitHub repositories.
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env-file-generator
Generate properly structured .env environment files with common variables, documentation comments, and secure placeholder patterns. Triggers on "create .env file", "generate environment variables", "env file for", "dotenv template".
ehtbanton/ClaudeSkillsRepo
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astro-page-generator
Generate Astro page components with islands architecture. Triggers on "create astro page", "generate astro component", "astro file", ".astro page".
ehtbanton/ClaudeSkillsRepo
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oauth-config-generator
Generate OAuth 2.0 configuration for social login providers (Google, GitHub, etc.). Triggers on "create oauth config", "generate oauth setup", "social login config", "oauth2 integration".
ehtbanton/ClaudeSkillsRepo
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circleci-config-generator
Generate CircleCI configuration files with workflows, orbs, and deployment. Triggers on "create circleci config", "generate circleci configuration", "circleci pipeline", "circle ci setup".
ehtbanton/ClaudeSkillsRepo
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delegation-advisor
Recommend who should do a task (Claude Code, Gemini, ChatGPT, Human, Taskmaster, MCPs) and generate handoff prompts.
omerreish-lgtm/secretary-system
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project-brief
Turn ideas/brain dumps into a structured project brief (problem, goals, scope, milestones, success criteria). Use when starting a project.
omerreish-lgtm/secretary-system
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skills-source-secretary-orchestrator
omerreish-lgtm/secretary-system
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task-engine
Create, organize, and prioritize tasks from briefs or brain dumps. Sync with Taskmaster MCP. Use to plan work, track status, and pick next steps.
omerreish-lgtm/secretary-system
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project-logger
Record project activity, decisions, and outputs; query history and status. Provides institutional memory across sessions.
omerreish-lgtm/secretary-system
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short-prompt-guide
Strategy for creating efficient short-form video prompts. Use when creating filler shots, atmospheric scenes, or quick video clips that don't require full Production Brief methodology. Covers when to go short vs long, format+style upfront rule, and two approaches (Descriptive vs Directive) for compact yet coherent results.
rfxlamia/flow 1
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arch-v
Video production workflow orchestrator for Veo 3. Guides users through creating professional video prompts via two paths - direct text-to-video OR image-to-video pipeline (Imagen 3/4 → Veo 3). Validates prompt completeness, checks conflicts, ensures all mandatory components present. Integrates camera-movements, great-prompt-anatomy, short-prompt-guide, long-prompt-guide, and imagine skills.
rfxlamia/flow 1
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camera-movements
Standardized camera movement vocabulary for Veo 3 video generation. Use when creating video prompts that require specific camera movements, cinematography terminology, or when validating camera movement specifications. Provides authoritative reference for 50+ camera movements (Dolly, Arc, Crane, FPV Drone, Whip Pan, etc.) to ensure consistent, production-ready terminology.
rfxlamia/flow 1
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storyteller
Transform abstract/metaphorical narrative into concrete visual story structure.
USE WHEN: Converting poetic/theatrical narrative from diverse-content-gen into scene-by-scene visual breakdowns ready for screenwriter formatting.
PIPELINE POSITION: diverse-content-gen → **storyteller** → screenwriter → production-validator → imagine → arch-v
PRIMARY FUNCTION: Bridge the gap between "altar pribadi" (abstract metaphor) and "woman returns daily to same beach spot" (filmable scene).
OUTPUT: Scene breakdown with concrete visual actions, preserved emotional core, and story logic documentation.
rfxlamia/flow 1
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long-prompt-guide
Production Brief methodology for complex Veo 3 video scenes. Use when creating scenes with dialogue, character continuity, structured settings, or multi-beat sequences. Provides 11-block framework (Format & Tone, Main Subjects, Wardrobe & Props, Location & Framing, Lighting & Palette, Continuity Rules, Actions & Camera Beats, Montage Plan, Dialogue, Sound & Foley, Finish) for professional, replicable results.
rfxlamia/flow 1
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great-prompt-anatomy
Essential framework for creating solid Veo 3 prompts. Use when constructing video prompts, validating prompt completeness, or teaching prompt structure. Defines 8 mandatory components (Subject, Setting, Action, Style/Genre, Camera/Composition, Lighting/Mood, Audio, Constraints) that every prompt must include for professional results.
rfxlamia/flow 1
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diverse-content-gen
Agent workflow for generating highly diverse creative content using Verbalized Sampling (VS) technique. Use when user requests multiple variations, brainstorming, creative ideas, or when standard prompting produces repetitive outputs. Increases diversity by 1.6-2.1× while maintaining quality. Works for: blog posts, social media captions, stories, campaign ideas, product descriptions, taglines, and open-ended creative tasks.
rfxlamia/flow 1
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imagine
Prepare detailed, professional prompts for Google Imagen 3/4 image generation. Supports character, environment, and object prompts using natural language with technical photography specifications. Extensible support for multiple art styles via reference files.
rfxlamia/flow 1
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production-validator
AI video pipeline validator for Veo 3 feasibility, 8-second scene chunking, and shot continuity.
USE WHEN: Validating screenplays for AI video generation, chunking scenes into 8-second segments, generating continuation prompts, scoring feasibility risk, or adding editing metadata.
PIPELINE POSITION: screenwriter → **production-validator** → imagine/arch-v
INPUT: XML from screenwriter skill (scene tags with duration, action, key_visuals) OUTPUT: Enhanced XML with validation, chunks, continuity tags, and Veo 3 prompts
KEY FUNCTIONS: - Veo 3 feasibility validation with risk scoring (LOW/MEDIUM/HIGH/CRITICAL) - 8-second scene chunking with continuation prompts - Shot continuity tagging for editors - Technical optimization for AI-friendly alternatives
rfxlamia/flow 1
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screenwriter
Transform creative ideas into professional, production-ready screenplays optimized for AI video generation pipelines. Converts raw concepts into structured scene-by-scene narratives with rich visual descriptions, proper screenplay formatting, and XML-tagged output for seamless integration with image/video generation tools (imagine, arch-v).
USE WHEN: Converting story ideas into screenplay format, preparing content for AI video pipelines, structuring narratives for 5-10 minute short films, generating visual-rich scene descriptions for image generation.
WORKFLOW: Raw idea → Scene breakdown → Visual enhancement → Professional formatting → XML-tagged markdown output
OUTPUT: Markdown document with XML-wrapped scenes, rich visual descriptions, proper screenplay elements (sluglines, action, dialogue), and metadata for pipeline processing.
rfxlamia/flow 1
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spec-driven-dev
Spec-Driven Development (SDD) agent for maintaining synchronized specifications, code, and documentation.
Core principle: "1 Todo = 1 Commit = 1 Spec Update".
Use this skill when:
- Starting a new feature or task that needs specification
- Implementing code based on existing specifications
- Validating that code matches specifications
- Updating CHANGELOG.md with changes
- Managing PRD/specification documents
- Ensuring traceability between requirements and implementation
Triggers: "spec", "specification", "PRD", "requirements", "SDD", "spec-driven"
TakukiN/skillport_tmp
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ui-designer
アプリケーションのUIデザイン方針を対話形式で決定する。
カラースキーム、レイアウト、コンポーネントスタイル、UXパターンなどを
ユーザーの好みに合わせて提案・調整する。
トリガー条件: (1)「デザインを変えたい」(2)「UIを改善したい」(3)「見た目を変更したい」(4)「テーマを変えたい」(5) デザインに関する相談
TakukiN/skillport_tmp
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requirements-definition
画像・動画共有システム（オンプレミス）の機能要件・非機能要件の定義を支援する。
要件のリストアップ、詳細説明、ベストプラクティスの提案を行う。
トリガー条件: (1)「機能要件を定義したい」(2)「非機能要件を定義したい」(3)「要件を確認したい」(4) 画像・動画共有システムの要件について質問されたとき
TakukiN/skillport_tmp
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notebook
Create professional Jupyter notebooks with zero-execution styling using markdown-based CSS and HTML components following Airbnb DLS principles.
sparkling/claude-config 1
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qlever
Query, configure, and optimize QLever—the high-performance open-source RDF triplestore. Covers SPARQL queries, GeoSPARQL, text search, CLI operations, and public endpoints. Informed by Kurt Cagle's semantic web expertise.
sparkling/claude-config 1